Size/position identification in real-time image processing using run length encoding

Messom, Chris; Demidenko, Serge; Subramaniam, Kamalraj; Gupta, Gourab Sen

doi:10.1109/imtc.2002.1007101

Cited by 18 publications

(10 citation statements)

References 6 publications

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“…We only mention the morphological filtering of objects, noise removal and geometric transforms as operations which can take advantage of this. For further uses of the run length encoding we refer to the papers Di Zenzo et al (1996) and Messom et al (2002). Since the recursive method of Martín-Herrero and ours follow in a way complementary ideas, a combination of both methods could be worth considering.…”

Section: Resultsmentioning

confidence: 99%

Labeling of N-Dimensional Images With Choosable Adjacency of the Pixels

Sandfort

Ohser

2011

Image Anal Stereol

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The labeling of discretized image data is one of the most essential operations in digital image processing. The notions of an adjacency system of pixels and the complementarity of two such systems are crucial to guarantee consistency of any labeling routine. In to date's publications, this complementarity usually is defined using discrete versions of the Jordan-Veblen curve theorem and the Jordan-Brouwer surface theorem for 2D and 3D images, respectively. In contrast, we follow here an alternative concept, which relies on a consistency relation for the Euler number. This relation and all necessary definitions are easily stated in a uniform manner for the n-dimensional case. For this, we present identification and convergence results for complementary adjacency systems, supplemented by examples for the 3D case. Next, we develop a pseudo-code for a general labeling algorithm. The application of such an algorithm should be assessed with regard to our preceding considerations. A benchmark and a thorough discussion finish our article.

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Section: Resultsmentioning

confidence: 99%

Labeling of N-Dimensional Images With Choosable Adjacency of the Pixels

Sandfort

Ohser

2011

Image Anal Stereol

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“…Accordingly, an image preprocessing selects the pixels whose signal-to-noise ratio (SNR) is greater than a user-defined detection threshold and discards the other ones [34]. This preliminary operation is referred to as segmentation and it is usually performed using a run-length encoding algorithm [35].…”

Section: Preprocessingmentioning

confidence: 99%

A geometrical approach for the angular velocity determination using a star sensor

Spiller

Curti

2022

Acta Astronautica

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“…Accordingly, an image preprocessing selects the pixels whose signal-to-noise ratio (SNR) is greater than a user-defined detection threshold and discards the other ones [23]. This preliminary operation is referred to as segmentation and it is usually performed using a run-length encoding algorithm [24].…”

Section: Preprocessingmentioning

confidence: 99%